import matplotlib.pyplot as plt

from myclasses.a5_result_methods import yield_results_for_noises_and_brains
from myclasses.a2_load_dataset import get_samples
from myclasses.a6_analyse.a1_output_accuracy import get_accuracy_to_noises_of_nodesizes

"""get_samples(scale_rate=100)

results = {}
for name, result in yield_results_for_noises_and_brains(
    sample_version='20220919',
    brains_version='20220918',
):
    results[name] = result"""

r = get_accuracy_to_noises_of_nodesizes('20220919', '20220919','20220918')

def draw(r):
    figure = plt.figure()
    for key in r[2]:
        plt.plot(r[2][key], label=str(key))
    plt.legend()
    return figure

def draw_(r, index=2):
    figure = plt.figure()
    for key in r[index]:
        plt.plot(r[index][key], label=str(key))
    plt.legend()
    return figure

print('hold on')
